ai-security

# AI Security AI and LLM security assessment skill for detecting prompt injection, jailbreak vulnerabilities, model inversion risk, data poisoning exposure, and agent tool abuse. This is NOT general application security (see security-pen-testing) or behavioral anomaly detection in infrastructure (see threat-detection) — this is about security assessment of AI/ML systems and LLM-based agents specifically. --- ## Table of Contents - [Overview](#overview) - [AI Threat Scanner Tool](#ai-threat-scanner-tool) - [Prompt Injection Detection](#prompt-injection-detection) - [Jailbreak Assessment](#jailbreak-assessment) - [Model Inversion Risk](#model-inversion-risk) - [Data Poisoning Risk](#data-poisoning-risk) - [Agent Tool Abuse](#agent-tool-abuse) - [MITRE ATLAS Coverage](#mitre-atlas-coverage) - [Guardrail Design Patterns](#guardrail-design-patterns) - [Workflows](#workflows) - [Anti-Patterns](#anti-patterns) - [Cross-References](#cross-references) --- ## Overview ### What This Skill Does This skill provides the methodology and tooling for **AI/ML security assessment** — scanning for prompt injection signatures, scoring model inversion and data poisoning risk, mapping findings to MITRE ATLAS techniques, and recommending guardrail controls. It supports LLMs, classifiers, and embedding models. ### Distinction from Other Security Skills | Skill | Focus | Approach | |-------|-------|----------| | **ai-security** (this) | AI/ML system security | Specialized — LLM injection, mo...